This library provides a Python interface to Google Analytics, supporting the Universal Analytics Measurement Protocol, with an interface modeled (loosely) after Google's analytics.js
.
NOTE this project is reasonably feature-complete for most use-cases, covering all relevant features of the Measurement Protocol, however we still consider it beta. Please feel free to file issues for feature requests.
Email: [email protected]
The easiest way to install universal-analytics is directly from PyPi using pip
by running the following command:
pip install universal-analytics-python
Or use latest code:
pip install -e git+https://github.com/analytics-pros/universal-analytics-python.git#egg=universal-analytics-python-dev
Otherwise you can download source code and install it directly:
python setup.py install
For the most accurate data in your reports, Analytics Pros recommends establishing a distinct ID for each of your users, and integrating that ID on your front-end web tracking, as well as back-end tracking calls. This provides for a consistent, correct representation of user engagement, without skewing overall visit metrics (and others).
A simple example:
from UniversalAnalytics import Tracker
tracker = Tracker.create('UA-XXXXX-Y', client_id = CUSTOMER_UNIQUE_ID)
tracker.send('event', 'Subscription', 'billing')
Please see the tests/main.py script for additional examples.
This library support the following tracking types, with corresponding (optional) arguments:
- pageview: [ page path ]
- event: category, action, [ label [, value ] ]
- social: network, action [, target ]
- timing: category, variable, time [, label ]
Additional tracking types supported with property dictionaries:
- transaction
- item
- screenview
- exception
Property dictionaries permit the same naming conventions given in the analytics.js Field Reference, with the addition of common spelling variations, abbreviations, and hyphenated names (rather than camel-case). These are also demonstrated in the tests/main.py file.
Further, the property dictionaries support names as per the Measurement Protocol Parameter Reference, and properties/parameters can be passed as named arguments.
Example:
# as python named-arguments
tracker.send('pageview', path = "/test", title = "Test page")
# as property dictionary
tracker.send('pageview', {
'path': "/test",
'title': "Test page"
})
- Throttling
We're particularly interested in the scope of throttling for back-end tracking for users who have a defined use-case for it. Please contact us if you have such a use-case.
universal-analytics-python is licensed under the BSD license